Tiger Data
Tiger Data builds PostgreSQL-based infrastructure for the operational data layer of the physical world, combining time-series, transactional, analytical, search, and agentic-AI workloads in one Postgres platform. Its products are designed for live machine and sensor data, real-time analytics, and AI applications without splitting data across specialized systems.
At a Glance
- Industrial and manufacturing companies
- Energy and utilities
- Oilfield services
- Renewable energy
- +6 more
AI Tools by Tiger Data
(1)
pgvectorscale
PostgreSQL Vector Search Extension
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Latest News
Announced pg_vectorsearch, a new open-source PostgreSQL vector-search extension using the PRISM index; said pgvectorscale will enter maintenance mode.
Launched TimescaleDB Enterprise, a self-managed commercial time-series database for on-premises, edge, and customer-managed cloud deployments.
Announced a strategic collaboration agreement with Amazon Web Services for modern Postgres infrastructure, integrations, Marketplace availability, and joint solutions.
Announced support for Amazon S3 Tables and Tiger Lake, connecting real-time Postgres with Apache Iceberg lakehouse infrastructure.
Products & Services
Open-source PostgreSQL extension for time-series data, providing hypertables/automatic time partitioning, compression, continuous aggregates, time-series functions, and fast real-time and historical analytics while retaining SQL and relational PostgreSQL compatibility.
Fully managed PostgreSQL/TimescaleDB service handling ingest, storage, live and historical queries, backups, upgrades, and scaling. It supports time-series, transactional, analytical, search, vector, and AI workloads.
Open-source PostgreSQL extension that builds on pgvector for higher-performance, cost-efficient embedding search. It adds StreamingDiskANN indexing, statistical binary quantization, and label-based filtered vector search; it runs in PostgreSQL and is written in Rust.
Open-source PostgreSQL extension for AI workflows including creating embeddings and obtaining model completions from PostgreSQL, supporting classification, summarization, enrichment, search, and RAG applications.
Market Position
Tiger Data positions itself as a PostgreSQL-native alternative to specialized time-series databases, general-purpose databases, and separate vector/search systems: it keeps relational context, SQL, and operational data in Postgres while adding time-series scale, compression, real-time analytics, search, and AI/vector capabilities. Its managed Tiger Cloud competes with services such as Amazon RDS/Aurora PostgreSQL and other managed time-series databases; pgvectorscale and pg_vectorsearch target vector databases and indexes such as Pinecone and HNSW on performance/cost.
Leadership
Founders
Ajay Kulkarni
Serial entrepreneur and product/company builder; previously co-founded iobeam and Sensobi, worked in product at GroupMe, and held roles at Microsoft, Citigroup, and startups. He studied computer science at MIT and earned an MIT Sloan degree.
Michael (Mike) Freedman
Computer-systems and networking researcher; Robert E. Kahn Professor of Computer Science at Princeton University, where he researches distributed systems, networking, and security. He is Tiger Data's co-founder and CTO.
Executive Team
Ajay Kulkarni
Founder and CEO
Serial entrepreneur and product/company builder; previously co-founded iobeam and Sensobi and worked at GroupMe, Microsoft, Citigroup, and startups.
Michael (Mike) Freedman
Founder and CTO
Robert E. Kahn Professor of Computer Science at Princeton University and researcher in distributed systems, networking, and security.
Board of Directors
Founding Story
Tiger Data began in 2015 as an IoT platform dealing with continuously arriving machine data from sensors and rapidly growing volumes. The founders found that existing databases forced a choice between reliable transactions and time-series scale, so they chose PostgreSQL as the trusted foundation and built TimescaleDB to make Postgres handle machine data at scale. The company later broadened from time-series into a modern PostgreSQL platform for analytical and agentic workloads.
Business Model
Revenue Model
Usage-based managed database subscriptions for Tiger Cloud, metered by compute and actual storage, plus paid enterprise subscriptions/support for TimescaleDB Enterprise and related services. TimescaleDB's open-source core is free; enterprise capabilities and production services are commercial.
Pricing Tiers
Hourly billing, 30-day free trial, single-node high-availability replicas, up to 3 days point-in-time recovery, Performance Insights, and basic 9-5 ET support.
Pay-as-you-go; adds multi-node high-availability replicas, up to 14 days point-in-time recovery, observability integrations, and integration/migration services.
Enterprise SLAs, production support, private networking/security options, and expert services.
Self-hosted open-source TimescaleDB.
Target Markets
- Industrial and manufacturing companies
- Energy and utilities
- Oilfield services
- Renewable energy
- Defense and regulated industries
- IoT and connected-device companies
- Industrial IoT and factory-floor telemetry
- Energy, utilities, oil and gas, renewable energy, and SCADA systems
- Robotics, connected devices, fleets, and physical-world operations
- IT, infrastructure, and network monitoring
- Real-time customer-facing analytics and dashboards
- Financial market data, risk analytics, and semantic search
- Fluke
- CERN
- Cloudflare
- Lucid Motors